1. Fields of the invention
The present invention relates to an image processing method, especially to a stereo matching method based on image intensity quantization.
2. Descriptions of Related Art
Besides the X axis and the Y axis of general two-dimensional images, visual elements of three-dimensional (3-D) images still includes depth perception, the visual ability to perceive the distance of objects in the images. The depth perception arises from various cues such as binocular disparity. Generally, the brain can detect small differences between the images of an object seen by each eye and combine the offset images to give the perception of 3-D depth.
Stereo matching techniques of nowadays are core techniques of digital photogrammetry and computer vision. Besides conventional way that computes stereo matching over a whole image, a plurality of area-based stereo matching algorithms such as segmentation algorithm, belief propagation, dynamic programming, etc that works on partial images have been developed.
In the segmentation algorithm, an image is segmented according to areas around objects contained in the image. The segmented areas with objects are processed and computed for stereo matching of the objects in some areas so as to create depth of objects in the image. As for the belief propagation, each pixel in the image is represented by a node. By calculating the relation between each node and neighboring nodes, stereo matching is performed on the partial area with object to create depth of objects in the image. The dynamic programming is a kind of recursive processing, repeatedly approaching a certain area of the image to get the optimal solution so as to create depth of objects in the image.
Compared with the conventional stereo matching method over the whole image, the area-based matching method is more accurate. Yet in the area-based matching method, disparity maps are output according to both the area-based matching results together with unmatched regions. Thus not only the computation is increased significantly, the computation time and the amount of processed image data are also increased dramatically. Although the processing accuracy of the stereo matching has been improved by the area-based matching method, a huge amount of information is generated during the stereo matching and computation time is increased.
In order to improve computational efficiency of the above stereo matching methods, several stereo matching techniques with iterative computation have been invented. One among them is through the use of an image pyramid. The image pyramid is a series of images at reduced scales, formed by repeatedly filtering and subsampling the original image in order to generate a sequence of reduced resolution images. Another way is to divide the image into a plurality of segments having foreground and background. Disparity maps between the foreground and background of different areas are obtained and merged so as to get a final result of image processing. Thereby, the computation during stereo matching is improved.
However, no matter the images reduced resolutions or segmented images, the above ways are focused on the image space. Although the computational efficiency is improved, the amount of processed image data during the matching is still quite huge. This has negative effects on data transmission and data access. Thus, for the images processed by conventional stereo matching, the network transmission is not convenient and the data access time is not reduced. For example, digital photogrammetry and computer vision, especially the popular 3-dimensional films (such as IMAX 3D movies), are the most well-known applications of computer vision. Yet the huge amount of data for stereo matching causes inconvenience for users to view 3-dimensional films on the interne or storage media at home.
Thus, there is a need to provide a stereo matching method based on image intensity quantization that provides a variate bit rate image processing for reducing the amount of image data. This helps data transmission as well as computational efficiency and solves the above shortcomings of conventional stereo matching.